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Cannabis Stocks Returns: The Role of Liquidity and Investors’ Attention via Google Metrics

Author

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  • Stephanos Papadamou

    (Laboratory of Economic Policy and Strategic Planning, Department of Economics, University of Thessaly, 38333 Volos, Greece)

  • Alexandros Koulis

    (Department of Regional Development, Ionian University, 31100 Lefkada, Greece)

  • Constantinos Kyriakopoulos

    (Department of Mathematics, National and Kapodistrian University of Athens, 15772 Athens, Greece)

  • Athanasios P. Fassas

    (Department of Accounting and Finance, University of Thessaly, 41500 Larissa, Greece)

Abstract

This paper studies one of the most popular investment themes over recent years, investing in the cannabis industry. In particular, it investigates relationships between investor attention, as proxied by Google Trends, and stock market activities, i.e., return, volatility, and liquidity. To this end, in the empirical analysis we study how liquidity and investors’ attention affect the return dynamics of an investment in cannabis stocks by augmenting the three-factor Fama–French model. In addition, we use a vector autoregressive approach and the impulse response function to measure shock transmission between the variables under consideration. Our empirical findings show that there is a statistically positive relationship between cannabis stock returns and liquidity. We also find that increased investors’ attention results in higher returns.

Suggested Citation

  • Stephanos Papadamou & Alexandros Koulis & Constantinos Kyriakopoulos & Athanasios P. Fassas, 2022. "Cannabis Stocks Returns: The Role of Liquidity and Investors’ Attention via Google Metrics," IJFS, MDPI, vol. 10(1), pages 1-11, January.
    • Handle: RePEc:gam:jijfss:v:10:y:2022:i:1:p:7-:d:717849
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    References listed on IDEAS

    as
    1. Vozlyublennaia, Nadia, 2014. "Investor attention, index performance, and return predictability," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 17-35.
    2. Ayad Assoil & Ndéné Ka & Jules Sadefo-Kamdem, 2021. "Analysis of the dynamic relationship between liquidity proxies and returns on the French CAC 40 index," SN Business & Economics, Springer, vol. 1(10), pages 1-23, October.
    3. Ayad Assoil & Ndéné Ka & Jules Sadefo Kamdem, 2021. "Analysis of the Dynamic Relationship between Liquidityproxies and returns on French CAC 40 index," Working Papers hal-03282991, HAL.
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    Cited by:

    1. Xu, Yingying & Dai, Yifan & Guo, Lingling & Chen, Jingjing, 2024. "Leveraging machine learning to forecast carbon returns: Factors from energy markets," Applied Energy, Elsevier, vol. 357(C).
    2. Fathin Faizah Said & Raja Solan Somasuntharam & Mohd Ridzwan Yaakub & Tamat Sarmidi, 2023. "Impact of Google searches and social media on digital assets’ volatility," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-17, December.
    3. Zheng, Yan & Wen, Fenghua & Deng, Hanshi & Zeng, Aiqing, 2022. "The relationship between carbon market attention and the EU CET market: Evidence from different market conditions," Finance Research Letters, Elsevier, vol. 50(C).

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